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Validation of Operational AMSR2 SSTs

Research Topic: Data Fusion and Algorithm Development
Task Leader: Andy Harris
CICS Scientist: Andy Harris
Sponsor: JPSSO
Published Date: 7/25/2014
AHAH_AMSR_tn

FY13 REPORT

BACKGROUND

The ability to retrieve SSTs even with 100% cloud cover is an invaluable asset for ocean forecasting and numerical weather prediction, especially during winter months.  For example, the ability to observe rapidly varying SSTs due to strong mixing during the passage of hurricanes is especially useful during the high activity phases of the hurricane season.  The AMSR-2 microwave imaging instrument can retrieve SSTs through clouds, and product is impervious to aerosol contamination.  In addition, AMSR-2 carries a new channel at 7.33 GHz which has the potential to assist in regions of light precipitation and in mitigating the effect of RFI contamination on the retrieval.  It is for these reasons that the timely provision of AMSR-2 SST observations is a highly desirable goal for a number of oceanographic, climate and weather applications.

ACCOMPLISHMENTS

The scope of the work is intended to encompass both validation and feedback for algorithm improvement.  Since we were only made aware of the provision of representative quality data in January 2014, and other projects had tight timelines (made even more demanding by personnel changes), and the project timeline runs July – June, only some of the intended analysis has been performed (sufficient to support NOAA’s algorithm readiness review) to date.  Key elements of our validation process are:

a)      Serves as validation of the end-product, and provides feedback for further adjustment and improvement, as required

b)      We found that comparison against Level-4 analyses is a very powerful tool to identify potential anomalies.

c)       Cross-comparison of errors identified in (d) against other derived parameters (wind speed, precipitation, cloud liquid water and water vapor) aids in discernment of cross-product feedback.

Figure 1 illustrates an apparent cross-product feedback (an warm bias in retrieved SST at low windspeeds).  A potential source of the observed bias might be a deficiency in an emissivity model (explicit or implicit).  However, since the bias is not observed in the nighttime data, it is much more likely that the observed biases are real, i.e. there is a geophysical explanation.  In this case, the candidate is the phenomenon of diurnal warming.

AHAH_AMSR_1

Figure 1. Bias in SST retrieved from AMSR with respect to OSTIA SST Analysis.  Left panel shows bias for daytime data while right panel shows the same plot for nighttime data.

PLANNED WORK

Below are the planned activities on this project.  Additional progress is anticipated on some of the following tasks, since they are being undertaken/completed this year (i.e. intended by end-June 2014)

  • Continue to refine analysis of AMSR-2 SST and BT products with the afore-mentioned tools to quantify: candidate calibration anomalies; geolocation/pointing errors; RFI contamination; inadequate rainfall flagging; and cross-product “interference”
  • Comparison of anomalies with other geophysical phenomena.  In particular, run our newly-developed global model of diurnal warming to account for possibility of low windspeed biases being due to geophysical differences
  • Report findings to JPSS AMSR-2 project: potential areas for improvement in Level 1 & Level 2 products; and iteration on validation of Level 1 & Level 2 product accuracies
  • As time permits, perform cross-comparison of AMSR-2 SSTs from Remote Sensing Systems with those from GAASP processing system, and ascertain most likely sources of product differences (retrieval algorithm, calibration differences)

PUBLICATIONS

None

DELIVERABLES

  • Report on GAASP AMSR-2 SST product accuracy;
  • Contribution of materials to NOAA design reviews.

PRESENTATIONS

None

OTHER

N/A

 

PERFORMANCE METRICS

 

FY13

# of new or improved products developed following NOAA guidance

0

# of products or techniques transitioned from research to ops following NOAA guidance

0

# of new or improved products developed without NOAA guidance

0

# of products or techniques transitioned from research to ops without NOAA guidance

0

# of peer reviewed papers

0

# of non-peered reviewed papers

0

# of invited presentations

0

# of graduate students supported by a CICS task

0

# of graduate students formally advised

0

# of undergraduate students mentored during the year

0

 

PERFORMANCE METRICS EXPLANATION

This task is only part of a major NOAA effort to produce SSTs (and other geophysical products) from AMSR-2 data.  Thus, while it contributes to that effort, no products are produced explicitly as part of this task.

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